Search: “reasoning”

arXiv:2605.14840v1 Announce Type: new Abstract: We study inventory control with decision-dependent censoring, focusing on the censored or repeated newsvendor (R-NV), where each order quantity determin

arXiv:2605.15184v1 Announce Type: new Abstract: Recent advances in Large Language Model (LLM) agents have enabled complex agentic workflows where models autonomously retrieve information, call tools,

arXiv:2605.14062v1 Announce Type: new Abstract: While synthetic data generation with large language models (LLMs) is widely used in post-training pipelines, existing approaches typically generate full

arXiv:2605.14483v1 Announce Type: new Abstract: Large language models (LLMs) have become a strong foundation for multi-agent systems, but their effectiveness depends heavily on orchestration design. A

arXiv:2602.16898v5 Announce Type: replace-cross Abstract: Task planning for robotic manipulation with large language models (LLMs) is an emerging area. Prior approaches rely on specialized models, fin

arXiv:2605.14781v1 Announce Type: new Abstract: Monocular 3D object detection remains challenging because metric size and depth are underdetermined by single-view evidence, particularly under occlusio

okay this email based mission control i prototypes last night is pretty cool: > starts with email > grab and summarize content about participants from crm/notes > auto bucket emails into workstreams u

arXiv:2605.14458v1 Announce Type: new Abstract: Omni-modal large language models have demonstrated remarkable potential in holistic multimodal understanding; however, the token explosion caused by hig

arXiv:2605.14374v1 Announce Type: cross Abstract: Pattern discovery in data plays a crucial role across diverse domains, including healthcare, risk assessment, and machinery maintenance. In contrast t

arXiv:2605.14055v1 Announce Type: cross Abstract: Parameter-Efficient Fine-Tuning (PEFT) is widely used for adapting Large Language Models (LLMs) for various tasks. Recently, there has been an increas

arXiv:2605.14561v1 Announce Type: new Abstract: Prompt engineering is crucial for effective interaction with generative artificial intelligence systems, yet existing optimisation methods often operate

arXiv:2510.20206v2 Announce Type: replace Abstract: Prompt design plays a crucial role in text-to-video (T2V) generation, yet user-provided prompts are often short, unstructured, and misaligned with t

arXiv:2605.14543v1 Announce Type: cross Abstract: Inpatient medication recommendation requires clinicians to repeatedly select specific medications, doses, and routes as a patient's condition evolves.

arXiv:2510.23818v2 Announce Type: replace Abstract: As large language models (LLMs) continue to scale in size, the computational overhead has become a major bottleneck for task-specific fine-tuning. W

arXiv:2605.14600v1 Announce Type: new Abstract: Scientific progress depends on sequences of enabling contributions, yet existing AI4Science benchmarks largely focus on citation prediction, literature

arXiv:2605.15026v1 Announce Type: cross Abstract: Online OS tuning can improve long-running services, but existing controllers are poorly matched to live hosts. They treat scheduler, power, memory, an

arXiv:2605.14089v1 Announce Type: new Abstract: In recent years, a variety of powerful LLM-based agentic systems have been applied to automate complex tasks through task orchestration. However, existi

arXiv:2510.13016v3 Announce Type: replace Abstract: A truly capable AI system must do more than detect objects or recognize activities in isolation. It must form unified, grounded representations of w

arXiv:2605.14604v1 Announce Type: new Abstract: This position paper argues that effective tutoring requires corrective friction: surfacing misconceptions and challenging them supportively to drive con

arXiv:2605.13909v1 Announce Type: cross Abstract: Negotiation is a central mechanism of economic exchange, shaping markets, procurement, labor agreements, and resource allocation. It is also a canonic

arXiv:2605.14477v1 Announce Type: new Abstract: We introduce EvoLib, a test-time learning framework that enables large language models to accumulate, reuse, and evolve knowledge across problem instanc

arXiv:2605.14164v1 Announce Type: new Abstract: The primary way to establish and compare competencies in foundation and generative AI models has shifted from peer-reviewed literature to press releases

arXiv:2603.18943v2 Announce Type: replace Abstract: This paper presents VGGT-360, a novel training-free framework for zero-shot, geometry-consistent panoramic depth estimation. Unlike prior view-indep

arXiv:2605.14290v1 Announce Type: cross Abstract: ReAct has become the default architecture across LLM agents, and many existing web agents follow this paradigm. We argue that it is the wrong default

arXiv:2605.13367v1 Announce Type: cross Abstract: The literature on ontology-mediated query answering (OMQA) has been shaped by two key results: first-order rewritability for DL-Lite, and PTime-hardne

arXiv:2605.12694v1 Announce Type: cross Abstract: Large language models can consult information that fixed static analyzers cannot, such as documentation, current security advisories, version-specific

Aleph is a fully autonomous AI agent system developed for formal verification that has achieved top performance across major theorem proving benchmarks, including PutnamBench and VeriSo. The system re

almost all LLM “thought” is derivative. below just sounds like hype to me 📁 Jensen Huang, CEO of NVIDIA, says GPT was never just about generating images or text but about generating thought itself. Th

arXiv:2605.13221v1 Announce Type: new Abstract: In cloud manufacturing, unmanned aerial vehicles (UAVs) can support both product collection and mobile edge computing (MEC). This joint operation forms

arXiv:2602.02560v2 Announce Type: replace-cross Abstract: Lung cancer remains the leading cause of cancer mortality, driving the development of automated screening tools to alleviate radiologist workl

arXiv:2605.06390v2 Announce Type: replace Abstract: A leading proposal for aligning artificial superintelligence (ASI) is to use AI agents to automate an increasing fraction of alignment research as c

arXiv:2605.13295v1 Announce Type: cross Abstract: LLM-based multi-agent systems have demonstrated strong performance across complex real-world tasks, such as software engineering, predictive modeling,

arXiv:2605.13646v1 Announce Type: cross Abstract: End-to-end autonomous driving, which bypasses traditional modular pipelines by directly predicting future trajectories from sensor inputs, has recentl

arXiv:2406.05410v3 Announce Type: replace Abstract: Current multimodal large language models (MLLMs) are mainly focused on the understanding and processing of perceptual modalities such as images and

arXiv:2511.00839v2 Announce Type: replace-cross Abstract: Current benchmarks for coding evaluate language models (LMs) on concrete, well-specified tasks such as fixing specific bugs or writing targete

arXiv:2605.13050v1 Announce Type: cross Abstract: Most existing large language models (LLMs) are expensive to adapt after deployment, especially when a task requires newly produced information or nich

arXiv:2605.13287v1 Announce Type: cross Abstract: Most exploration algorithms search broadly until uncertainty is resolved. When the action space is too large to resolve within budget, practitioners d

.@Discoplomacy This kill-switch provision helps govt intervene in cases where UK datacenters are being maliciously used by a threat actor to conduct cyberattacks. It also helps in cases where the gove

arXiv:2605.13156v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated remarkable capabilities in bridging visual perception and natural language understanding, enabling a wid

arXiv:2605.13485v1 Announce Type: new Abstract: Transformers predict over a representation of a sequence. The same data can be written as bytes, characters, or subword tokens, and these representation

arXiv:2602.22455v2 Announce Type: replace Abstract: We investigate the feasibility of using Multimodal Large Language Models (MLLMs) for real-time online episodic memory question answering. While clou

arXiv:2509.23056v2 Announce Type: replace Abstract: Remote sensing object detection is a critical technology for real-world applications such as natural resource monitoring, traffic management, and UA

arXiv:2605.12826v1 Announce Type: cross Abstract: The proliferation of sophisticated image editing tools and generative artificial intelligence models has made verifying the authenticity of digital im

arXiv:2603.26839v2 Announce Type: replace-cross Abstract: How do multimodal models solve visual spatial tasks -- through genuine planning, or through brute-force search in token space? We introduce ex

arXiv:2605.13821v1 Announce Type: new Abstract: Agentic evolution has emerged as a powerful paradigm for improving programs, workflows, and scientific solutions by iteratively generating candidates, e

// Harnessing Agentic Evolution // Pay attention to this one if you run iterative agentic search loops. (bookmark it) AEvo splits the self-improvement loop into two jobs: > One proposes the next candi